Data Validation is the process of making sure that the data has been checked for errors. Keeping in view the volume of data available with business organisations, manual data validation becomes quite a herculean task. Manual validation ensures that the data is in-house and secure, yet the fact that it is error prone and cumbersome makes automation necessary. Every bit of data is of paramount importance and even a small mistake can put the businesses at great risk. In order to make data validation easy and speedy, new software platforms are emerging. These software platforms are resilient, mature, scalable, and sufficiently reliable.
Automated Data Validation
Automation of data validation makes use of digital transformation technology. This is revolutionizing the way in which businesses carry out their operations. It ensures that the data has undergone data cleansing and keeps the data quality in check.
Automated Data Validation = Data Cleansing + Data Quality
- Data Cleansing
As the data undergoes cleansing, the inaccurate, incomplete, incorrect, incomplete and irrelevant parts of the data are identified and corrected. The dirty or coarse data due to user-entry errors or corruption in transmission or storage is modified, replaced or deleted. The cleansed data is consistent with other data sets in the system. The basic difference between data validation and cleansing is that, validation rejects the data at entry. Data validation is performed at the time of entry rather than on the batches of data as in data cleansing. Validation confirms the data quality in terms of validity, completeness, accuracy, consistency and uniformity.
- Data Quality
Automated data validation makes sure that the data in the automated system is both, correct and useful. Validation can be performed for the data type, range and constraints, code and cross reference, and structure. Data validation includes validation check and the post-check action. Validation check uses computational rules to check if the data is valid and the post-check action sends feedback to enforce the validation.
How Automated Data Validation Works?
Automation of data validation helps in the efficient execution of high value work. It liberates the employees from repetitive and mundane tasks in their jobs so that they can perform work that has higher value and greater significance. If the data validation is not automated, qualified employees end up staying engaged in robotic data entry tasks of standardizing, re-formatting and merging the data with larger sets in order to make it useful. This eats up the quality time that the skilled employees would have otherwise spent on work that makes the best use of their skills, skills they were actually hired for.
Automated data validation is a part of business process automation based on software robots or Artificial Intelligence. It is the integration of new technology into the current working environment. Automation of data validation develops the action list by watching the real user perform a particular task in the Graphical User Interface (GUI) of an application. It then performs the automation of process under consideration, directly in the Graphical User Interface.
Benefits of Automated Data Validation:
Automation of data validation has the following benefits:
- Data Volume
The amount of data available with the business organisations today is huge. Performing the data validation manually is not only difficult but it is also prone to inevitable human errors.
- Data Quality
Automation of data validation ensures the quality of data. The validated data is accurate, valid, complete, consistent and uniform.
- Merges and Acquisitions
As one business merges with another business or acquires another business, lots of data becomes obsolete. At times, the data is useful and has to be combined to give meaning to it. Performing these tasks manually is time consuming and requires much effort. Despite this, the data fitness, accuracy and consistency is not guaranteed.
As automated tasks can be done without much human help, this makes them a lot more dependable. The employees and businesses can rely on them for the execution of various routine tasks.
- Risk Reduction
Manual data validation is prone to risks of bias, variation and fatigue. Automated validation of data reduces the risk of manipulation of data to a great extent. The total risk faced by the businesses is thereby reduced.
- Migration of Data Centers
In case of migration of data centres of business, the data is prone to the risk of corruption in transmission and storage. Automated validation helps in easy validation of data in such cases.
- Improves Effeciency
Automation of tasks like data validation saves a lot of effort, time and energy of the employees. The cost associated with learning new technology and automation of data validation is nothing when compared to the benefits. This makes automation of data validation an efficient upgrade for the businesses.
- More Symantic
As the process is automated, the steps to be performed are laid out well in advance. All the instructed steps are performed at all times, for all data. Automation makes everything more systematic.
- Saves Times
As the data validation process is automated, the employees can devote their time in doing work that actually uses their core skills. This saves their time which would otherwise have been spent on repetitive tasks.
- Minimum Effort Required
The process is automated once and all the data is validated. Moreover, automation of data validation is scalable.
Automated Process as a Teammate:
As already outlined, automation of data validation can help save time, money and effort and ensures maximum efficiency for the business. In a world where all business decisions and actions are data driven, automation of data validation cannot be overlooked.
There are still people who are of the opinion that artificial intelligence and automation of processes can result in layoffs. However, it is time businesses understood that Artificial Intelligence and Automation of processes has the power to take the robot out of people! The internal human resource can be used for better work than just maintenance and upkeep of data. This will give them more time for performing the interpersonal roles.
To conclude, automated data validation results in more work and higher productivity with the same headcount in the organisation.